Repeated Measures ANOVA (Non-parametric)

The Friedman test is used to explore the relationship between a continuous dependent variable and a categorical explanatory variable, where the explanatory variable is ‘within subjects’ (where multiple measurements are from the same subject). It is analagous to Repeated Measures ANOVA, but with the advantage of being non-parametric, and not requiring the assumptions of normality or homogeneity of variances. However, it has the limitation that it can only test a single explanatory variable at a time.

Example usage

data('bugs', package = 'jmv')

anovaRMNP(bugs, measures = vars(LDLF, LDHF, HDLF, HDHF))

#  Friedman
#  ────────────────────────
#    χ²      df    p
#  ────────────────────────
#    55.8     3    < .001
#  ────────────────────────


data the data as a data frame
measures a vector of strings naming the repeated measures variables
pairs TRUE or FALSE (default), perform pairwise comparisons
desc TRUE or FALSE (default), provide descriptive statistics
plots TRUE or FALSE (default), provide a descriptive plot
plotType 'means' (default) or 'medians', the error bars to use in the plot


A results object containing:

results$table a table
results$comp a table
results$desc a table
results$plot an image

Tables can be converted to data frames with asDF or For example: